In addition, frequency-related cues are increasingly important for forgery detection since it's hard to find visual forgery clues.
Although some studies [1]}, [2]}, [3]}, [4]} have introduced frequency information and achieved remarkable results,
their abilities to extract discriminative features are limited because of employing fixed filter banks and hand-crafted features.
These methods based on incomprehensive prior knowledge are insufficient to capture subtle forgery patterns from the frequency domain due to the diversity of background, gender, age, manipulation methods, \(\)
